Numpy 2.0 compatibility

[saitcakmak]

While reviewing pytorch/botorch#2293, I noticed test failures coming from cma due to incompatibility with Numpy 2.0. One thing led to another and here we are with a PR making cma compatible with Numpy 2.0.

Changelist:

• Replace array(…, copy=False) with np.asarray(…)
• Replace np.Inf with np.inf
• Replace np.alltrue with np.all
• Replace np.NaN with np.nan

Test fixes:

• list(np.ndarray) returns [np.float64(value), …] rather than [value, …]. So, using np.ndarray.tolist() instead.
• Similarly, functions return np.float64(value), which are compared to native float values.
• Add .item() calls to approx_equal to make it return native True rather than np.True_

Test plan:

• pip install numpy==2.0.0rc1
• python -m cma.test

[nikohansen]

This looks like a bug: np.asarray doesn't accept a copy argument?

[saitcakmak]

Nice catch! I'll change this to array(x, copy=True) to make it clear that it's only called when copy=True.

[nikohansen]

Thanks a lot! Looks good beside the small point I commented on.

Another question: did you consider using float(.) instead of .item() when a np.float64 is expected? I guess both has pros and cons.

[saitcakmak]

Another question: did you consider using float(.) instead of .item() when a np.float64 is expected? I guess both has pros and cons.

I haven't thought of using float(.), just went with .item() since that's what I am used to using with numpy & pytorch. I guess it wouldn't make a meaningful difference since the changes are contained to doctests -- though I don't really know how different the two are under the hood.